manim-mcp / orchestrator.py
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Fix NameError: Import Callable from typing
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"""
NeuroAnim Orchestrator
This script coordinates the entire STEM animation generation pipeline:
1. Concept Planning
2. Code Generation
3. Rendering
4. Vision-based Analysis
5. Audio Generation
6. Final Merging
It uses the MCP servers (renderer and creative) to accomplish these tasks.
"""
import ast
import asyncio
import json
import logging
import os
import tempfile
from pathlib import Path
from typing import Any, Dict, List, Optional, Callable
import aiofiles
from dotenv import load_dotenv
from mcp import ClientSession, StdioServerParameters
from mcp.client.stdio import stdio_client
from utils.tts import TTSGenerator
load_dotenv()
# Set up logging
logging.basicConfig(
level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s"
)
logger = logging.getLogger(__name__)
class NeuroAnimOrchestrator:
"""Main orchestrator for NeuroAnim pipeline."""
def __init__(
self, hf_api_key: Optional[str] = None, elevenlabs_api_key: Optional[str] = None
):
self.hf_api_key = hf_api_key or os.getenv("HUGGINGFACE_API_KEY")
self.elevenlabs_api_key = elevenlabs_api_key or os.getenv("ELEVENLABS_API_KEY")
self.renderer_session: Optional[ClientSession] = None
self.creative_session: Optional[ClientSession] = None
# Initialize TTS generator
self.tts_generator = TTSGenerator(
elevenlabs_api_key=self.elevenlabs_api_key,
hf_api_key=self.hf_api_key,
fallback_enabled=True,
)
# Context managers for MCP client connections
self._renderer_cm = None
self._creative_cm = None
self._renderer_streams = None
self._creative_streams = None
# Working directories
self.work_dir: Optional[Path] = None
self.output_dir: Optional[Path] = None
async def initialize(self):
"""Initialize MCP server connections."""
# Set up working directories
self.work_dir = Path(tempfile.mkdtemp(prefix="neuroanim_work_"))
self.output_dir = Path("outputs")
self.output_dir.mkdir(exist_ok=True)
logger.info(f"Working directory: {self.work_dir}")
logger.info(f"Output directory: {self.output_dir}")
# Initialize renderer server
# stdio_client is an async context manager, must use async with
renderer_params = StdioServerParameters(
command="python", args=["mcp_servers/renderer.py"]
)
self._renderer_cm = stdio_client(renderer_params)
self._renderer_streams = await self._renderer_cm.__aenter__()
read_stream, write_stream = self._renderer_streams
self.renderer_session = ClientSession(read_stream, write_stream)
# Start background receive loop for the client session
await self.renderer_session.__aenter__()
await self.renderer_session.initialize()
logger.info("Renderer MCP server connected")
# Initialize creative server
creative_params = StdioServerParameters(
command="python",
args=["mcp_servers/creative.py"],
env={"HUGGINGFACE_API_KEY": self.hf_api_key} if self.hf_api_key else None,
)
self._creative_cm = stdio_client(creative_params)
self._creative_streams = await self._creative_cm.__aenter__()
read_stream, write_stream = self._creative_streams
self.creative_session = ClientSession(read_stream, write_stream)
# Start background receive loop for the client session
await self.creative_session.__aenter__()
await self.creative_session.initialize()
logger.info("Creative MCP server connected")
async def cleanup(self):
"""Clean up resources."""
import shutil
# Close sessions first
if self.renderer_session:
try:
await self.renderer_session.__aexit__(None, None, None)
except (Exception, asyncio.CancelledError) as e:
logger.debug(f"Error closing renderer session: {e}")
if self.creative_session:
try:
await self.creative_session.__aexit__(None, None, None)
except (Exception, asyncio.CancelledError) as e:
logger.debug(f"Error closing creative session: {e}")
# Then close the stdio_client context managers with timeout
if self._renderer_cm:
try:
async with asyncio.timeout(2): # 2 second timeout
await self._renderer_cm.__aexit__(None, None, None)
except (Exception, asyncio.CancelledError, TimeoutError) as e:
logger.debug(f"Error closing renderer context manager: {e}")
if self._creative_cm:
try:
async with asyncio.timeout(2): # 2 second timeout
await self._creative_cm.__aexit__(None, None, None)
except (Exception, asyncio.CancelledError, TimeoutError) as e:
logger.debug(f"Error closing creative context manager: {e}")
# Clean up working directory
if self.work_dir and self.work_dir.exists():
try:
shutil.rmtree(self.work_dir)
logger.info(f"Cleaned up working directory: {self.work_dir}")
except Exception as e:
logger.warning(f"Failed to clean up working directory: {e}")
async def call_tool(
self, session: ClientSession, tool_name: str, arguments: Dict[str, Any]
) -> Dict[str, Any]:
"""Call a tool on an MCP server."""
result = await session.call_tool(tool_name, arguments)
if hasattr(result, "content") and result.content:
content = result.content[0]
if hasattr(content, "text"):
return {
"text": content.text,
"isError": getattr(result, "isError", False),
}
return {"text": str(result), "isError": False}
async def generate_animation(
self,
topic: str,
target_audience: str = "general",
animation_length_minutes: float = 2.0,
output_filename: str = "animation.mp4",
quality: str = "medium",
progress_callback: Optional[Callable[[str, float], None]] = None,
) -> Dict[str, Any]:
"""Complete animation generation pipeline."""
def report_progress(step: str, progress: float):
if progress_callback:
try:
progress_callback(step, progress)
except Exception as e:
logger.warning(f"Progress callback failed: {e}")
try:
logger.info(f"Starting animation generation for: {topic}")
report_progress("Planning concept", 0.1)
# Step 1: Concept Planning
logger.info("Step 1: Planning concept...")
concept_result = await self.call_tool(
self.creative_session,
"plan_concept",
{
"topic": topic,
"target_audience": target_audience,
"animation_length_minutes": animation_length_minutes,
},
)
if concept_result["isError"]:
raise Exception(f"Concept planning failed: {concept_result['text']}")
concept_plan = concept_result["text"]
logger.info("Concept planning completed")
report_progress("Generating narration script", 0.25)
# Step 2: Generate Narration
logger.info("Step 2: Generating narration...")
narration_result = await self.call_tool(
self.creative_session,
"generate_narration",
{
"concept": topic,
"scene_description": concept_plan,
"target_audience": target_audience,
"duration_seconds": int(animation_length_minutes * 60),
},
)
if narration_result["isError"]:
raise Exception(
f"Narration generation failed: {narration_result['text']}"
)
narration_text = narration_result["text"]
logger.info("Narration generation completed")
report_progress("Creating Manim animation code", 0.40)
# Step 3: Generate Manim Code with retry logic
logger.info("Step 3: Generating Manim code...")
manim_code = await self._generate_and_validate_code(
topic=topic, concept_plan=concept_plan, max_retries=3
)
logger.info("Manim code generation completed and validated")
# Step 4: Write Manim File
logger.info("Step 4: Writing Manim file...")
manim_file = self.work_dir / "animation.py"
write_result = await self.call_tool(
self.renderer_session,
"write_manim_file",
{"filepath": str(manim_file), "code": manim_code},
)
if write_result["isError"]:
raise Exception(f"File writing failed: {write_result['text']}")
# Extract scene name from code
scene_name = self._extract_scene_name(manim_code)
logger.info(f"Scene name detected: {scene_name}")
report_progress("Rendering animation video", 0.55)
# Step 5: Render Animation
logger.info("Step 5: Rendering animation...")
render_result = await self.call_tool(
self.renderer_session,
"render_manim_animation",
{
"scene_name": scene_name,
"file_path": str(manim_file),
"output_dir": str(self.work_dir),
"quality": quality,
"format": "mp4",
"frame_rate": 30,
},
)
if render_result["isError"]:
raise Exception(f"Rendering failed: {render_result['text']}")
# Find rendered video file
video_file = self._find_output_file(self.work_dir, scene_name, "mp4")
if not video_file:
raise Exception("Could not find rendered video file")
logger.info(f"Animation rendered: {video_file}")
report_progress("Generating audio narration", 0.75)
# Step 6: Generate Speech Audio
logger.info("Step 6: Generating speech audio...")
audio_file = self.work_dir / "narration.mp3"
# Use TTS generator with automatic fallback
try:
tts_result = await self.tts_generator.generate_speech(
text=narration_text, output_path=audio_file, voice="rachel"
)
logger.info(
f"Audio generated with {tts_result['provider']}: {audio_file}"
)
# Validate audio file
validation = self.tts_generator.validate_audio_file(audio_file)
if not validation["valid"]:
logger.warning(
f"Audio validation warning: {validation.get('error', 'Unknown issue')}"
)
logger.info("Audio file may have issues but continuing...")
else:
logger.info(
f"Audio validated: {validation.get('duration', 'N/A')}s, {validation.get('size', 0)} bytes"
)
except Exception as e:
logger.error(f"TTS generation failed: {e}")
raise Exception(f"Speech generation failed: {str(e)}")
report_progress("Merging video and audio", 0.90)
# Step 7: Merge Video and Audio
logger.info("Step 7: Merging video and audio...")
final_output = self.output_dir / output_filename
merge_result = await self.call_tool(
self.renderer_session,
"merge_video_audio",
{
"video_file": str(video_file),
"audio_file": str(audio_file),
"output_file": str(final_output),
},
)
if merge_result["isError"]:
raise Exception(f"Merging failed: {merge_result['text']}")
logger.info(f"Final video created: {final_output}")
report_progress("Creating quiz questions", 0.95)
# Step 8: Generate Quiz
logger.info("Step 8: Generating quiz...")
quiz_result = await self.call_tool(
self.creative_session,
"generate_quiz",
{"topic": topic, "target_audience": target_audience},
)
quiz_content = (
quiz_result["text"] if not quiz_result["isError"] else "Not available"
)
report_progress("Finalizing", 1.0)
return {
"success": True,
"output_file": str(final_output),
"topic": topic,
"target_audience": target_audience,
"concept_plan": concept_plan,
"narration": narration_text,
"manim_code": manim_code,
"quiz": quiz_content,
}
# Step 8: Generate Quiz
logger.info("Step 8: Generating quiz...")
quiz_result = await self.call_tool(
self.creative_session,
"generate_quiz",
{
"concept": topic,
"difficulty": "medium",
"num_questions": 3,
"question_types": ["multiple_choice"],
},
)
quiz_content = (
quiz_result["text"]
if not quiz_result["isError"]
else "Quiz generation failed"
)
# Return results
results = {
"success": True,
"topic": topic,
"target_audience": target_audience,
"concept_plan": concept_plan,
"narration": narration_text,
"manim_code": manim_code,
"output_file": str(final_output),
"quiz": quiz_content,
"work_dir": str(self.work_dir),
}
logger.info(f"Animation generation completed successfully: {final_output}")
return results
except Exception as e:
logger.error(f"Animation generation failed: {str(e)}")
return {
"success": False,
"error": str(e),
"work_dir": str(self.work_dir) if self.work_dir else None,
}
def _extract_python_code(self, response_text: str) -> str:
"""Extract Python code from markdown response."""
# Look for code blocks
if "```python" in response_text:
start = response_text.find("```python") + 9
end = response_text.find("```", start)
if end == -1:
end = len(response_text)
return response_text[start:end].strip()
elif "```" in response_text:
start = response_text.find("```") + 3
end = response_text.find("```", start)
if end == -1:
end = len(response_text)
return response_text[start:end].strip()
else:
return response_text.strip()
async def _generate_and_validate_code(
self,
topic: str,
concept_plan: str,
max_retries: int = 3,
previous_error: Optional[str] = None,
previous_code: Optional[str] = None,
) -> str:
"""Generate Manim code with retry logic for syntax errors."""
for attempt in range(max_retries):
try:
logger.info(f"Code generation attempt {attempt + 1}/{max_retries}")
# Build arguments for code generation
arguments = {
"concept": topic,
"scene_description": concept_plan,
"visual_elements": ["text", "shapes", "animations"],
}
# If this is a retry, include error feedback
if previous_error and previous_code:
arguments["previous_code"] = previous_code
arguments["error_message"] = previous_error
logger.info(
f"Retrying with error feedback: {previous_error[:100]}..."
)
# Generate code
code_result = await self.call_tool(
self.creative_session, "generate_manim_code", arguments
)
if code_result["isError"]:
if attempt < max_retries - 1:
logger.warning(
f"Code generation failed, retrying: {code_result['text']}"
)
previous_error = code_result["text"]
continue
else:
raise Exception(
f"Code generation failed: {code_result['text']}"
)
# Extract Python code from response
manim_code = self._extract_python_code(code_result["text"])
# Validate Python syntax
syntax_errors = self._validate_python_syntax(manim_code)
if syntax_errors:
if attempt < max_retries - 1:
logger.warning(
f"Syntax error detected, retrying: {syntax_errors}"
)
previous_error = f"Syntax Error:\n{syntax_errors}"
previous_code = manim_code
continue
else:
raise Exception(
f"Generated code has syntax errors after {max_retries} attempts:\n{syntax_errors}"
)
# Success!
logger.info(f"Valid code generated on attempt {attempt + 1}")
return manim_code
except Exception as e:
if attempt < max_retries - 1:
logger.warning(f"Attempt {attempt + 1} failed: {str(e)}")
previous_error = str(e)
continue
else:
raise
raise Exception("Failed to generate valid code after all retries")
def _validate_python_syntax(self, code: str) -> Optional[str]:
"""Validate Python code syntax. Returns error message if invalid, None if valid."""
try:
ast.parse(code)
return None
except SyntaxError as e:
error_msg = f"Line {e.lineno}: {e.msg}"
if e.text:
error_msg += f"\n {e.text.rstrip()}"
if e.offset:
error_msg += f"\n {' ' * (e.offset - 1)}^"
return error_msg
except Exception as e:
return f"Unexpected error during syntax validation: {str(e)}"
def _extract_scene_name(self, code: str) -> str:
"""Extract scene class name from Manim code."""
import re
# Look for class definition that inherits from Scene, MovingCameraScene, etc.
match = re.search(r"class\s+(\w+)\s*\(\s*\w*Scene\s*\)", code)
if match:
return match.group(1)
return "Scene" # fallback
def _find_output_file(
self, directory: Path, scene_name: str, extension: str
) -> Optional[Path]:
"""Find output file with given scene name and extension."""
for file in directory.glob(f"{scene_name}*.{extension}"):
return file
return None
async def main():
"""Main function for running the orchestrator."""
import argparse
parser = argparse.ArgumentParser(description="NeuroAnim STEM Animation Generator")
parser.add_argument("topic", help="STEM topic for the animation")
parser.add_argument(
"--audience",
choices=["elementary", "middle_school", "high_school", "college", "general"],
default="general",
help="Target audience",
)
parser.add_argument(
"--duration", type=float, default=2.0, help="Animation duration in minutes"
)
parser.add_argument("--output", default="animation.mp4", help="Output filename")
parser.add_argument(
"--api-key", help="Hugging Face API key (or set HUGGINGFACE_API_KEY env var)"
)
parser.add_argument(
"--elevenlabs-key",
help="ElevenLabs API key (or set ELEVENLABS_API_KEY env var)",
)
args = parser.parse_args()
# Initialize and run orchestrator
orchestrator = NeuroAnimOrchestrator(
hf_api_key=args.api_key, elevenlabs_api_key=args.elevenlabs_key
)
try:
await orchestrator.initialize()
results = await orchestrator.generate_animation(
topic=args.topic,
target_audience=args.audience,
animation_length_minutes=args.duration,
output_filename=args.output,
)
if results["success"]:
print("\n🎉 Animation Generated Successfully!")
print(f"📹 Output file: {results['output_file']}")
print(f"🎯 Topic: {results['topic']}")
print(f"👥 Audience: {results['target_audience']}")
print(f"\n📝 Concept Plan:")
print(
results["concept_plan"][:500] + "..."
if len(results["concept_plan"]) > 500
else results["concept_plan"]
)
print(f"\n🎭 Narration:")
print(
results["narration"][:300] + "..."
if len(results["narration"]) > 300
else results["narration"]
)
print(f"\n📚 Quiz Questions:")
print(results["quiz"])
else:
print(f"\n❌ Animation Generation Failed: {results['error']}")
except KeyboardInterrupt:
print("\n⚠️ Process interrupted by user")
except Exception as e:
print(f"\n💥 Unexpected error: {str(e)}")
finally:
await orchestrator.cleanup()
if __name__ == "__main__":
asyncio.run(main())